Role

We're looking for a Staff Backend Engineer - Data Platform to be a key technical leader within the teams responsible for Depop's data platform. You'll drive the technical vision and implementation for our foundational data platform - from experimentation, event ingestion pipelines to our data lake, governance frameworks, and data observability and real-time analytics capabilities.

You will work closely with data scientists, machine learning engineers, backend teams, and product leaders, providing deep technical expertise to ensure our data systems are scalable, secure, observable, and enable innovation across the company.

Responsibilities

• Partner with stakeholders across Product, Data, and Engineering to translate strategic goals into well-architected, scalable platform capabilities.
• Drive the technical design and implementation of core data platform components, providing hands-on coding and architectural leadership.
• Define and evolve the technical roadmap for Depop's modern data platform, ensuring reliable and scalable analytics.
• Champion engineering excellence, setting high technical standards and advocating for best practices in system design, maintainability, performance, and privacy.
• Lead efforts in data observability, governance, and privacy-by-design principles, ensuring their robust implementation across the organization.
• Mentor and coach engineers, elevating the technical capabilities of the team and fostering a culture of technical excellence.
• Identify and address complex technical challenges and bottlenecks, proposing and implementing effective solutions.

• Proven experience as a Staff Engineer or equivalent senior technical leadership role in data infrastructure or platform at scale, ideally in a consumer or marketplace environment.
• Deep understanding of distributed systems and modern data ecosystems - including extensive experience with Databricks, Apache Spark, Apache Kafka, Apache Flink, Apache Beam and DBT.
• Demonstrated success in designing, building, and operating data platforms at scale, encompassing both batch processing and real-time streaming architectures.
• Expertise in data warehousing concepts, advanced ETL/ELT processes, and analytics engineering best practices.
• Exceptional programming skills, particularly in Python, Scala, or Java, and deep expertise with cloud platforms (AWS, GCP, or Azure).
• Extensive experience working with privacy-sensitive datasets and implementing robust data observability and governance frameworks.
• A strong technical background with a track record of hands-on architecture and development of complex data systems.
• Ability to think strategically and pragmatically: you can define long-term technical strategies and execute rapidly.
• Excellent communication and collaboration skills; you're comfortable influencing technical direction and aligning diverse stakeholders across the organization.

• Experience with machine learning infrastructure or ML Ops practices.
• Familiarity with event-driven architectures in a mobile-first product environment.
• Prior work in fashion, marketplaces, or sustainability-driven tech.